A number of technological and economic barriers currently exist in the development of new types of electronic devices and systems. As devices approach the atomic scale, they become noisy and prone to faults in production and use. Opposite to the consumer trend of price reduction, the cost for producers to fulfill Moore's law is increasing dramatically. At the same time, however, it is also becoming increasingly clear that current computing approaches will not meet the challenges brought by adaptive autonomous controllers. The power-discrepancy between a biological solution and an advanced computing system is so large that it points to flaws in notions of computing.
FIG. 1 illustrates a graph 100 depicting power-discrepancy between biological solutions and advanced computing systems, in accordance with the disclosed embodiments. For example, consider a human body simulated at a moderate fidelity such that each cell of the body is allocated to one CPU and that the distance between a memory and a processor is distance d. At an operating voltage V=1 and d=1 cm, the simulation would consume at minimum 100 GW of power, or about the total peak power consumption of France in 2011. If the voltage is lowered to a thermodynamic limit of V=0.025V (kT at room temperature) and the CPU-memory distance to the diameter of an average cell, d=10−5 m, it will still consume 62.5 kW, which is 625 times as much energy as is actually consumed by the human body. The distance between the CPU and memory must be at least 2 nm or less for the simulation to equal the efficiency of biology if the operating voltage is set to 70 mV, the resting potential of a neuron. The progromatic paradigm breaks down at such low voltages since the barrier energy between bit states becomes comparable to the thermal energy. For these reason, it's relatively clear that a new type of computing system based on self-organization of nature must be created. While some point to quantum computing as a potential solution, it must be noted that the extreme isolations required to maintain a qubit in its superposition state are at odds with the solution which has clearly been found by life, which is heavily integrated with its environment and operates in extremely volatile conditions. What is needed is a solution based more on the self-repairing and self-assembling properties of life while still integrating with modern electronics.
Nature is capable of building structures of far greater complexity than any modern chip and it is capable of doing it while embedded in the real world. If the principles of autonomous self-organization are illuminated, it can cascade through all parts of world economy. Self organizing circuits can dramatically reduce the cost of fabrication by increasing yields as the circuits can adapt around faults. Any application that must interact with a complex changing environment is a potential platform for the self-organizing autonomous control circuitry. The ability to heal, a natural consequence of an attractor-based self-organization, leads to enhanced survival in hostile environments.
Based on the foregoing, it is believed that a need exists for an improved system and method for achieving self organized growth of a logic and/or algorithmic pathways. A need also exists for an improved physically-self-organized circuit fabric system that interacts dynamically to growth algorithms and continuously self-repairs if damaged, as described in greater detail herein.